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Alibaba · 480B parameters (35B active) · coding.
Ollama weight files: Q4_K_M 290 GB (qwen3-coder:480b); Q8_0 510 GB (qwen3-coder:480b-a35b-q8_0).
Yes on 5 machines in this list. The smallest is 4x Mac Studio M5 Max (40c GPU) 128GB: Q5_K_M, about 342.8 GB, roughly 7 tokens per second, via llama.cpp. llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node
llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other nodeexo # on every Mac (brew install --cask exo); load mlx-community/Qwen3-Coder-480B-A35B-Instruct-4bit with Tensor sharding + RDMA| Hardware | Runtime | Quant | Memory | Fit | Speed | Command |
|---|---|---|---|---|---|---|
| 4x Mac Studio M5 Max (40c GPU) 128GB | llama.cpp | Q5_K_M GGUF | 342.8 GB | fits in fast memory | ~7 tok/s | llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
| 2x Mac Studio M5 Ultra (80c GPU) 256GB | llama.cpp | Q5_K_M GGUF | 342.8 GB | fits in fast memory | ~16 tok/s | llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q5_K_M --rpc node2:50052 -c 8192 # run rpc-server on each other node |
| Mac Studio M3 Ultra (80c GPU) 512GB | Ollama | Q4_K_M | 292.4 GB | fits in fast memory | ~15 tok/s | ollama run qwen3-coder:480b |
| 4x DGX Spark 128GB | llama.cpp | Q5_K_M GGUF | 342.8 GB | fits in fast memory | ~5 tok/s | llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q5_K_M --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
| 4x Mac Studio M5 Ultra (80c GPU) 256GB | llama.cpp | Q8_0 GGUF | 512.7 GB | fits in fast memory | ~10 tok/s | llama-server -hf unsloth/Qwen3-Coder-480B-A35B-Instruct-GGUF:Q8_0 --rpc node2:50052,node3:50052,node4:50052 -c 8192 # run rpc-server on each other node |
Estimates, not benchmarks. Model sizes are ollama.com download sizes; memory needed adds headroom for ~8k tokens of context; speeds are rough figures from memory bandwidth. Data updated 2026-10-16.
A project by OnDevice Labs · llms.txt